2016 SU2C Sharp Awards
Defining the Role of Epigenetics in Chimeric Antigen Receptor T-cell Therapy for CLL
Shelley Berger, PhD, University of Pennsylvania
Carl June, MD, University of Pennsylvania
Grant Term: May 2016 – April 2017
Total Funding: $200,000
Despite considerable success of the CART-19 approach in acute lymphoblastic leukemia (ALL), the same CART-19 treatment induces remission in approximately 40 perent of chronic lymphocytic leukemia (CLL) subjects, while approximately 60 percent eventually progress with disease. The weaker efficacy in CLL can either be due to tumor resistance because of epigenetic silencing (inactivation of genes resulting from DNA modifications) of tumor targets of the CAR T cells, conditions in the tumor microenvironment, or to inherent characteristics of the CAR T cells. CAR T cells may be less effective when their ability to kill cancer cells is unstable, when they do not persist in circulation long enough to kill the cancer cells, or when the gene that they carry is shut off. Drs. Berger and June hypothesize that many, if not all, of these potential resistance mechanisms are due to modifications in the DNA.
Drs. Berger and June studied CAR T cells from CLL patients who responded to the therapy. They observed that these cells express genes that allow them to kill cancer cells effectively, and genes that enable them to persist long enough in the circulation of patients.
Drs. Berger and June identified two classes of proteins that can regulate T cell function – TET2 and BET proteins. Disrupting TET2, a DNA modifying protein, resulted in potentially superior antitumor activity. BET protein inhibition, on the other hand, can reduce the expression of proteins that hinder T cells from doing their job. These proteins, called checkpoint inhibitors, are TIM-3 and PD-1.
The promising results obtained from this Sharp Award laid the foundation for an SU2C-Lustgarten Foundation Research Team project. The project seeks to develop CAR T-based therapeutic strategies for pancreatic cancer.
Towards Predictive Models of Immunotherapy Response
Benjamin D. Greenbaum, PhD, Icahn School of Medicine at Mount Sinai
Jedd D. Wolchok, MD, PhD, Memorial Sloan Kettering Cancer Center
Grant Term: May 2016 – April 2018
Total Funding: $200,000
When this project was conceptualized, it was unclear whether one can predict patient response to immunotherapy from knowing the genetic characteristics of a patient’s tumor. There are data that indicate that patients with tumors that have a higher number of mutations may be more responsive to immunotherapy. Nevertheless, a consensus has not emerged on how to best utilize patient genomic information to build predictive models for patient response. In this proposal, Drs. Greenbaum and Wolchok proposed to develop a predictive model of response to checkpoint blockade immunotherapies.
The team has developed a model to predict response to checkpoint blockade. They confirmed that their model is predictive of response, by validating it using data from three different patient groups: two melanoma cohorts treated with anti-CTLA-4, and one lung cancer cohort treated with anti-PD-1.
The team found that their model was able to predict long-term survivors of pancreatic cancer, regardless of the treatment that the patients received.
The team’s work in long-term survivors of pancreatic cancer is being continued with the support of an SU2C Convergence grant.